Add FastSAM and YOLO-World tracking docs (#10733)

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

docs/en/models/fast-sam.md

@@ -119,6 +119,30 @@ Validation of the model on a dataset can be done as follows:
 
 Please note that FastSAM only supports detection and segmentation of a single class of object. This means it will recognize and segment all objects as the same class. Therefore, when preparing the dataset, you need to convert all object category IDs to 0.
 
+### Track Usage
+
+To perform object tracking on an image, use the `track` method as shown below:
+
+!!! Example
+
+    === "Python"
+   
+        ```python
+        from ultralytics import FastSAM
+
+        # Create a FastSAM model
+        model = FastSAM('FastSAM-s.pt')  # or FastSAM-x.pt
+
+        # Track with a FastSAM model on a video
+        results = model.track(source="path/to/video.mp4", imgsz=640)
+        ```
+   
+    === "CLI"
+
+        ```bash
+        yolo segment track model=FastSAM-s.pt source="path/to/video/file.mp4" imgsz=640
+        ```
+
 ## FastSAM official Usage
 
 FastSAM is also available directly from the [https://github.com/CASIA-IVA-Lab/FastSAM](https://github.com/CASIA-IVA-Lab/FastSAM) repository. Here is a brief overview of the typical steps you might take to use FastSAM:

docs/en/models/yolo-world.md

@@ -152,6 +152,31 @@ Model validation on a dataset is streamlined as follows:
         yolo val model=yolov8s-world.pt data=coco8.yaml imgsz=640
         ```
 
+### Track Usage
+
+Object tracking with YOLO-World model on a video/images is streamlined as follows:
+
+!!! Example
+
+    === "Python"
+
+        ```python
+        from ultralytics import YOLO
+
+        # Create a YOLO-World model
+        model = YOLO('yolov8s-world.pt')  # or select yolov8m/l-world.pt for different sizes
+
+        # Track with a YOLO-World model on a video
+        results = model.track(source="path/to/video.mp4")
+        ```
+
+    === "CLI"
+
+        ```bash
+        # Track with a YOLO-World model on the video with a specified image size
+        yolo track model=yolov8s-world.pt imgsz=640 source="path/to/video/file.mp4"
+        ```
+
 !!! Note
 
     The YOLO-World models provided by Ultralytics come pre-configured with [COCO dataset](../datasets/detect/coco.md) categories as part of their offline vocabulary, enhancing efficiency for immediate application. This integration allows the YOLOv8-World models to directly recognize and predict the 80 standard categories defined in the COCO dataset without requiring additional setup or customization.